CN-121971102-A - Three-dimensional electrocardiogram imaging method, device and medium based on dynamic atrial model

CN121971102ACN 121971102 ACN121971102 ACN 121971102ACN-121971102-A

Abstract

The application discloses a three-dimensional electrocardiogram imaging method, device and medium based on a dynamic atrial model, which relate to the technical field of electrocardiogram imaging and comprise the steps of collecting atrial multi-phase image data and physiological state related data, wherein the physiological state related data at least comprises respiratory signals and body position change data; the method comprises the steps of constructing an initial dynamic atrial model based on atrial multi-temporal image data in combination with a self-adaptive grid optimization technology, optimizing the shape and the position of the initial dynamic atrial model through a self-adjusting geometric optimization algorithm by utilizing physiological state related data, generating an electric activity transmission matrix based on the optimized dynamic atrial model, wherein the electric activity transmission matrix is used for describing the transmission characteristics of atrial electric activity, and realizing three-dimensional electrocardiographic imaging through solving an electrocardiographic inverse problem based on electric activity transmission matrix and body surface potential signals. The application can improve the solving precision of the ECGI inverse problem.

Inventors

ZHANG YADAN
CUI HE
CUI YANGYANG
XU DONG
ZHAO YONGQIANG
WANG GUOTAI
PANG MAOTONG
HAN XIAOLE
DU LING
CUI WENZHAO

Assignees

杭州极弱磁场国家重大科技基础设施研究院

Dates

Publication Date: 20260505
Application Date: 20251205

Claims (10)

1. A method of three-dimensional electrocardiographic imaging based on a dynamic atrial model, comprising: Collecting atrial multi-phase image data and physiological state related data, wherein the physiological state related data at least comprises respiratory signals and body position change data; based on the atrial multi-temporal image data, constructing an initial dynamic atrial model by combining an adaptive grid optimization technology; Optimizing the shape and the position of the initial dynamic atrial model by using the physiological state related data through a self-adjusting geometric optimization algorithm; Generating an electrical activity transfer matrix based on the optimized dynamic atrial model, wherein the electrical activity transfer matrix is used for describing transfer characteristics of atrial electrical activity; Based on the electric activity transmission matrix and the body surface potential signals, three-dimensional electrocardiographic imaging is realized through electrocardiographic imaging inverse problem solving.
2. The method of claim 1, wherein the acquiring atrial multi-phase image data and physiological state related data comprises: Determining a plurality of critical phases within an atrial cardiac cycle, the critical phases encompassing at least end systole and end diastole; CT or MRI scanning is respectively carried out on the plurality of key phases, and corresponding atrial multi-phase image data are obtained; Physiological state related data are collected by body surface sensors.
3. The method of claim 1, wherein constructing an initial dynamic atrial model based on the atrial multi-temporal image data in combination with an adaptive mesh optimization technique comprises: Registering the preprocessed atrial multi-temporal image data to ensure the spatial consistency of different temporal images; analyzing the atrial geometry of each key time phase based on the registered atrial multi-time phase image data; Generating a high-density grid in an atrial key region and a low-density grid in a flat region by adopting an adaptive grid generation algorithm based on the atrial geometric characteristics; Carrying out three-dimensional reconstruction on the atrium of each key time phase according to grid distribution and the multi-time-phase image data of the atrium; and integrating the three-dimensional reconstruction results of each key time phase to form an initial dynamic atrial model which can be changed along with the cardiac cycle.
4. The method of claim 1, wherein using the physiological state related data to morphologically and positionally optimize the initial dynamic atrial model by a self-adjusting geometry optimization algorithm comprises: Based on the acquired respiratory signals and body position change data, establishing a dynamic change model of the atrial position; taking the dynamic change model as a reference, executing a morphological and positional optimization process on the initial dynamic atrial model by adopting a corresponding strategy according to the sequence of scaling, rotation and displacement, and acquiring electric activity feedback information, wherein the optimization process comprises kinematic constraint, smooth transition treatment and electric activity feedback iteration; Judging the adjustment effect of the current strategy based on the electric activity feedback information, switching to the next strategy if the current strategy can not improve the electric activity envelope continuity, and iteratively adjusting the model parameters until the electric activity feedback information meets the preset standard, and judging that the initial dynamic atrium model is adapted to the current physiological state to obtain the optimized dynamic atrium model.
5. The method of claim 1, wherein generating an electrical activity transfer matrix based on the optimized dynamic atrial model comprises: performing electrophysiological modeling on the optimized dynamic atrium model to obtain electrophysiological parameters corresponding to each atrium grid point, wherein the electrophysiological parameters comprise tissue conductivity, cell potential and current density; Taking time domain change and space distribution characteristics of electric activity into consideration, and establishing a time-space coupling optimization model; based on the coupling optimization model, combining the model geometric form and the electrophysiological parameters to initially construct an electric activity transfer matrix; And (3) based on a preset multi-optimization target, performing iterative optimization on the preliminarily constructed electric activity transfer matrix through a global optimization algorithm to obtain an optimized electric activity transfer matrix.
6. The method of claim 1, wherein three-dimensional electrocardiography imaging is achieved by inverse problem solution of electrocardiography imaging based on the electrical activity transfer matrix and body surface potential signals, comprising: Collecting a body surface potential signal of a human body, and carrying out filtering pretreatment on the body surface potential signal; inputting the preprocessed body surface potential signals into an optimized electric activity transmission matrix, solving an electrocardiographic imaging inverse problem, and reconstructing epicardial potential; Extracting an electrical activity envelope of the reconstructed epicardial potential; evaluating whether envelope characteristics of the electrical activity envelope meet preset optimization criteria; And if the envelope characteristic meets the preset optimization standard, generating three-dimensional electrocardiographic imaging data based on the reconstructed epicardial potential.
7. The method of claim 6, wherein evaluating whether the envelope characteristics of the electrical activity envelope meet preset optimization criteria comprises: performing multi-scale decomposition on the extracted electric activity envelope to obtain envelope signals with different frequency components; calculating the second derivatives of envelope signals of different frequency components, and obtaining a second derivative evaluation result by calculating the absolute value mean value of the second derivatives; Performing feature analysis on envelope signals of different frequency components to identify potential mutation points; Scoring the continuity and smoothness of different frequency components based on the second derivative evaluation result and the mutation point identification result; weighting and summing the scores of the frequency components to obtain an overall evaluation score of the electric activity envelope; If the overall evaluation value is greater than or equal to a preset threshold value, judging that the characteristics of the electric activity envelope meet a preset optimization standard; And if the overall evaluation value is smaller than the preset threshold value, judging that the envelope characteristic of the electric activity envelope does not meet a preset optimization standard.
8. A three-dimensional electrocardiographic imaging device based on a dynamic atrial model, comprising: The acquisition module is used for acquiring atrial multi-temporal image data and physiological state related data, wherein the physiological state related data at least comprises respiratory signals and body position change data; The construction module is used for constructing an initial dynamic atrial model based on the atrial multi-temporal image data and combining an adaptive grid optimization technology; the optimization module is used for optimizing the shape and the position of the initial dynamic atrial model through a self-adjusting geometric optimization algorithm by utilizing the physiological state related data; a generation module for generating an electrical activity transfer matrix based on the optimized dynamic atrial model, the electrical activity transfer matrix describing transfer characteristics of atrial electrical activity; And the imaging module is used for realizing three-dimensional electrocardiographic imaging through electrocardiographic imaging inverse problem solving based on the electric activity transmission matrix and the body surface potential signals.
9. A storage medium having stored thereon a computer program, which when executed by a processor, implements the method of any of claims 1 to 7.
10. An electronic device comprising a storage medium, a processor and a computer program stored on the storage medium and executable on the processor, characterized in that the processor implements the method of any one of claims 1 to 7 when executing the computer program.

Description

Three-dimensional electrocardiogram imaging method, device and medium based on dynamic atrial model Technical Field The application relates to the technical field of electrocardiographic imaging, in particular to a three-dimensional electrocardiographic imaging method, device and medium based on a dynamic atrial model. Background The electrocardio imaging (Electrocardiographic Imaging, ECGI) technology is used as a noninvasive and accurate heart electric activity detection means, and has important value in clinical diagnosis and treatment guidance of cardiovascular diseases such as arrhythmia, atrial fibrillation and the like. The heart function evaluation method based on the inverse problem is characterized in that the electric activity state of the heart surface is reconstructed by collecting potential signals of the body surface of a human body and solving the inverse problem, so that visual evaluation basis of the heart electrophysiological function is provided for a clinician. In the ECGI inverse problem solving process, the accuracy of the geometric form of the atrial model and the rationality of the transfer matrix directly determine the accuracy of the electrical activity reconstruction, so that the construction of the model capable of truly reflecting the physiological state of the atrium becomes a key link for improving the clinical application value of the ECGI technology. With the development of medical imaging technology and computational simulation technology, the ECGI technology has gradually become a research hotspot in the field of cardiovascular disease diagnosis, and the demand for high-precision atrial models is becoming urgent. In the prior art, the construction of an atrial model mainly depends on static image data such as cardiac computed tomography or magnetic resonance imaging, and the geometric form of an atrium in a specific time phase (such as end systole or end diastole) is obtained through an image reconstruction algorithm, so that an electric activity transmission matrix is constructed based on the static form. In order to optimize the model precision, a part of schemes adopt the traditional optimization means such as a geometric correction method and the like to finely adjust the space position of the static model so as to reduce the deviation between the model and the actual anatomical structure of the human body. However, these solutions all use static geometry as a core, and do not fully consider dynamic variation factors in the physiological process of the human body. The key technical problem in the prior art is that the atrium is an important component of the heart, the geometric form of the atrium can accompany regular systolic and diastolic movements in the cardiac cycle, and the atrium can also be subjected to position deviation under the influence of physiological factors such as respiratory rhythm, body position change and the like. The existing static atrial model can not dynamically simulate the geometric form and position change in the physiological process, so that the constructed transfer matrix is difficult to accurately describe the transfer characteristics of the electric activity under different physiological states. Even if the traditional geometric correction method can optimize the position deviation of a static model, the problem that the model is not matched with the actual atrial morphology caused by dynamic change cannot be fundamentally solved, the problem that the ECGI inverse problem is solved is insufficient finally, the reconstructed heart surface electric activity deviates from the actual physiological state, and the severe requirement of clinical diagnosis on accuracy is difficult to meet. Disclosure of Invention In view of the above, the application provides a three-dimensional electrocardiographic imaging method, a device and a medium based on a dynamic atrial model, which can improve the solving precision of ECGI inverse problems. According to a first aspect of the present application, there is provided a three-dimensional electrocardiographic imaging method based on a dynamic atrial model, comprising: Collecting atrial multi-phase image data and physiological state related data, wherein the physiological state related data at least comprises respiratory signals and body position change data; based on the atrial multi-temporal image data, constructing an initial dynamic atrial model by combining an adaptive grid optimization technology; Optimizing the shape and the position of the initial dynamic atrial model by using the physiological state related data through a self-adjusting geometric optimization algorithm; Generating an electrical activity transfer matrix based on the optimized dynamic atrial model, wherein the electrical activity transfer matrix is used for describing transfer characteristics of atrial electrical activity; Based on the electric activity transmission matrix and the body surface potential signals, three-dimensional el